Video streams are nowadays often detected for monitoring specific areas. These areas can be, e.g., areas in which there is a risk of theft such as in sales areas in retailing, or outer areas of facilities to be protected such as storage buildings, airports or military facilities. Monitoring is improved if more as well as more efficient cameras are available, so that a relatively high resolution is possible and non-monitored areas can be reduced in size or avoided.
However, it is not sufficient to only direct a camera to areas of interest. Because of the thus generated large data volumes it should rather be possible to differentiate in the video streams between relevant and irrelevant information, i.e. identify activities of interest.
In many cases, for example in perimeter monitoring, it is mainly of interest whether there are movements in an area or not. In such a case, for example, an alarm can be triggered or the storage of data can be initiated. It is pointed out that data storage, alarm triggering, etc. caused by the detection of a movement can also be coupled to the additional occurrence of specific signals of other sensors, detectors or general signaling devices such as heat alarms, smoke alarms or data relating to retailing actions such as “till open” or “price tag of article XY scanned”. It is pointed out that this can offer advantages also with the present invention, also advantages being essential to the invention.
Movements of objects lead to image changes that can be determined per se. It is known to carry out extensive analyses in the image in order to recognize “background”, define “objects” in front of the background, e.g., by edge detection, and then monitor the movement of the respective objects over several frames, which is done in particularly demanding applications also by updating background changes. While such methods are per se able to recognize the movements of objects, they are complex. This is disadvantageous if recognition should take place directly in the camera, because much computing power is necessary in this case. This means increased hardware requirements and increased energy consumption. Even if recognition should not take place in the camera itself but, e.g., in a central unit, this is disadvantageous because as a rule large data volumes accumulate therein and processing thereof in turn leads to considerable processing requirements.
Therefore, it is desirable to be able to detect movements of objects well. A good detection is achieved, i.a., if movement of those objects which are of particular interest is recognized with at best few false alarms and nevertheless little data processing requirements.
It is the object of the present invention to provide novel subject-matter for industrial applications.
This object is achieved in independent form. Preferred embodiments can be found in the dependent claims.